Examining the Biases Driving Hate Crime in the United States and How People Respond on Social Media

By Shraddha Jhingan, Sofia Maysenhalder, Tammie Tam

March 14, 2022

Introduction

In 2020, the number of reported hate crimes in the United States rose 6 percent from 2019, according to the FBI (Hernandez 2021). About 62 percent of reported hate crimes were racially motivated (FBI). In a study examining the role of social media on the frequency of hate crime in Germany, the researchers found an increased anti-refugee rhetoric and sentiments on social media has been correlated with an increased frequency in anti-refugee hate crimes in Germany (Müller and Schwarz 2021). On the flip side, we wonder how has most everyday people responded to such hate crime incidents on social media. Therefore, we are interested in the understanding the biases that motivate hate crime and how people fight against it on social media in the United States.

Using datasets on hate crime cases from the FBI's Crime Data Explorer page and Sacramento's police department, we hope to answer the following questions at the National (U.S.), State (California), and City (Sacramento) level:

Using the Reddit API, we hope to answer the following questions at the State (California) and City (Sacramento) level:

By answering these questions using data analysis and visualization methods, we hope to understand ways hate crimes can be prevented and where we can target hate-crime-prevention policies.

Analysis/Visualization

USA Hate Crimes

Data Collection + Cleaning

To obtain data about hate crimes in the United States and California, we are using the Federal Bureau of Investigation’s 1991-2020 Hate Crime Dataset (hc), which is downloadable from their Crime Data Explore webpage (FBI Crime Data Explorer). The dataset contains pertinent information, such as the year, the motivation ("bias_desc"), and location ("state_abbr", "pub_agency_name"), on reported hate crimes across the U.S from 1991-2020. Through this dataset, we want to explore which types of biases are the strongest driving factors in hate crime and how the nature of these hate crimes vary across the United States.

The dataset is overall complete, but has a few formatting issues. The column names were in inconsistent letter casing, so we made them all lower cases, and renamed column names to make them more simplistic, such as renaming “data_year” to “year”. Missing values and unnecessary columns were removed from the dataset. One interesting thing is that “Nebraska” was abbreviated “NB” when the official abbreviation for it is “NE.” This was an issue when trying to generate maps that relied on the official abbreviation, so this issue was fixed by replacing “NB” for “NE” in the “state_abbr” column. Since there were so many different specific biases, each bias was assigned a bias category for a more standardized analysis. Some reported hate crime incidents had more than one bias, so these were removed since they were only a few and would make subsequent visualizations more messy.

Data Analysis and Visualization

To analyze hate crime in the United States, I attempted to answer the following questions:

  1. How has the number of hate crimes changed over the years?
  2. How do the number of reported hate crimes by bias category change each year?
  3. Within the race/ethnicity (“race/ethn”) bias category, how does racial bias change over time?
  4. How much did the number of hate crime incidents by race/ethnicity change from 2019 to 2020?
  5. In each state, how many hate crimes due to race/ethnicity has there been in total since 1991 until 2020?
  6. In each state, how many hate crimes due to race/ethnicity are there in 2020?

In the United States, the number of hate crimes increased from 1991 to 2001 and then steadily decreased until 2015. In 2015, the number of hate crimes increased dramatically, reaching an all time high in 2020.

US_1

The dramatic increase in the number of reported hate crimes is due to an increase in the number of racially motivated hate crimes. Other motivators of hate crime such as a person’s sex, sexuality, religion, and disability have remained relatively stabled across the three decades.

Total Number of Hate Crimes By Motivation in the U.S. Between 1991-2020 Change in Total Number of Hate Crimes By Motivation in the U.S. Between 1991-2020
US_2a US_2b

Since race/ethnicity is a significant motivator in hate crime and the main driver in the increase in the number of hate crimes, understanding which anti-race/ethnicity bias is most prevalent is important. The top 5 anti-races/ethnicities biases in hate crimes from most to least are Anti-Black, Anti-White, Anti-Hispanic or Latino, Anti-Other Race/Ethnicity/Ancestry, and Anti-Asian. Out of the 5, anti-Black biases dominate significantly and are the main driver in hate crimes biased by race/ethnicity from 1991 to 2020.

Total Number of Hate Crimes By Racial Motivation in the U.S. Between 1991-2020 Change in Number of Hate Crimes By Different Racial Motivation in the U.S. Between 1991-2020
US_3 US_4

From 2019 to 2020, hate crimes against almost all races except for Arab increased. The top 5 race/ethnicities that experienced an uptick in hate crimes are those of Multiple Races, White, Asian, Black or African American, and Eastern Orthodox. According to the BBC, the rise in hate crimes against Asians is due to the misinformation and negative attention brought about by the COVID-19 pandemic, since COVID-19 originated from China (Cabral 2021). Since the Black Lives Matter Movement that started in 2013, more attention--good and bad--have been placed on Black people. According to Dr. Emmitt Y. Riley, III, this has led to racial tension and resentment from White people, which may contribute to the rise in hate crime against Black people (UC Press 2021). The rise in anti-White hate crimes is surprising at first glance. But according to the Daily Beast, white nationalist groups are spinning stories of hate crimes against White people, which may have led to over-reporting anti-White hate crimes (Hay 2021).

|Percent Difference in Number of Hate Crime Incidents By Racial Motivators from 2019-2020 in U.S.|

|US_5|

Since 1991, hate crimes due to racial biases have occurred in every state, but have occurred the most in California, the most populous state (World Population Review).

Click for interactive map: Total Number of Hate Crime Incidents By State since 1991 USmap

Even in 2020, California remains a leading state in hate crimes, with New York coming in a close second.

Click for interactive map: Total Number of Hate Crime Incidents By State in 2020 USmap

California Hate Crimes

Data Collection + Cleaning

When examining the data on California, there were many cities so we grouped them by counties and the type of counties such as urban, suburban, and rural. To obtain information to cross reference city to county, the 2020_CA_city_to_county.csv (CA_c2c) dataset was obtained from World Population Review (World Population Review). This dataset contains information on which cities are in which counties. The counties were grouped into “urban”, “suburban”, and “rural” (CA State Association of Counties).

To make the California-only hate crime dataset, I subsetted the national hate crime dataset from the FBI by selecting rows with “CA” in the “state_abbr” column. On top of this, I cross referenced the city and county from the hate crime dataset to the CA_c2c dataset and added two columns “county” and “county_cat” to provide information on the county name of that city and the type of county it belongs to. Since there were some reported hate crime incidents that did not report back a city or county name, I removed those from the dataset.

Data Analysis and Visualization

To analyze hate crime in California, I attempted to ask similar questions as at the U.S. level:

  1. How has the number of hate crimes changed over the years?
  2. How do the numbers of reported hate crimes by bias category change each year?
  3. Within the race/ethnicity (“race/ethn”) bias category, how does racial bias change over time?
  4. How much did the number of hate crime incidents by racial motivations change from 2019 to 2020?
  5. What are the major biases motivating hate crime in urban, suburban, and rural counties?
  6. Does the number of hate crimes motivated by race/ethnicity vary between urban, suburban, and rural counties?
  7. In each county in CA, how many hate crimes due to race/ethnicity are there in total since 1991?
  8. In each county in CA, how many hate crimes due to race/ethnicity are there in 2020?

Following the national trend, the number of hate crimes in California increased until around 2001, and decreased until 2015 before picking back up.

CA_1

Since 1991, the top three biases fueling hate crimes include race/ethnicity, sexuality, and religion. Hate crimes against race/ethnicity are the most common across all years since 1991. Proportion-wise, hate crimes against race/ethnicity occur at a lesser rate than on a national level. Anti-race/ethnicity bias in hate crimes is one of the only biases to experience a significant increase around 2020, once again demonstrating anti-race/ethnicity bias to be the largest driver in the number of reported hate crimes.

Total Number of Hate Crimes By Motivation in CA. Between 1991-2020 Change in Total Number of Hate Crimes By Motivation in CA Between 1991-2020
CA_2 CA_3

Similar to hate crimes across the U.S. the top 5 racial motivators from highest to lowest is anti-Black or African American, Anti-Hispanic or Latino, Anti-Asian, Anti-White, and Anti-Other Race/Ethnicity/Ancestry. One main difference is that hate crimes against Hispanics or Latinos are more common than one would think from examining the patterns at the national level. This may be because California has one of the largest Hispanic and Latino populations (Statista 2019).

Total Number of Hate Crimes By Racial Motivation in CA. Between 1991-2020 Change in Total Number of Hate Crimes By Racial Motivation in CA Between 1991-2020
CA_4 CA_5

From 2019 to 2020, hate crimes against all races except for Arab and Multiple Race increased. Hate crimes against Arabs decreased, while hate crimes against those of multiple races remained the same. The most noteworthy increase is that hate crimes against Asians increased by nearly 120 percent. One reason for this is the start of the COVID-19 pandemic in 2020 that drew a lot of negative attention and attitudes towards Asians and those of Asian descent. Since California has the highest Asian population out of all the states, an increase in hate crimes against Asians is not surprising (World Population Review 2022). New stories of attacks on Asians have dominated the news cycle in many major California cities like Sacramento and Los Angeles (Mizes-Tan 2021, Cosgrove 2021).

|Percent Difference in Number of Hate Crimes by Racial Motivators from 2019 to 2020 in CA|

|CA_6|

Across urban, suburban, and rural counties, hate crimes against race/ethnicity dominate on top of other biases. Similarly, hate crimes against sexuality and religion follow as the next most common hate crimes.

CA_7a

CA_7b

CA_7c

Since urban counties have higher populations, they have the highest number of hate crimes from 1991-2020. Interestingly, only hate crimes in urban counties follow the trend found at the national and state level, such that there is an increase in hate crime until 2001 and then a decrease until around 2014 before increasing again. This trend is not found in suburban or rural counties. As a result, hate crimes in urban counties have the greatest impact on the trend seen at the state level.

CA_8

Totaling the number of hate crimes from 1991 to 2020, most counties in California have comparable levels of hate crimes, but Los Angeles and San Diego County stand out with much higher levels of hate crimes against race/ethnicity. This may be attributed to the two counties having a high population (California Demographics 2020).

Click for interactive map: Total Number of Hate Crime Incidents in CA since 1991

Even in 2020, this pattern still stands with Los Angeles county and San Diego county having higher levels of racially motivated hate crimes.

Click for interactive map: Total Number of Hate Crime Incidents in CA in 2020

Sacramento Hate Crimes

Data Collection + Cleaning

To analyze hate crimes in Sacramento, we will use the Sacramento Police Department's Incidence Reports between 2017 and 2021 for our analysis, which can be found on their Crime and Statistics page (Sacramento Crime Data). Since the individual incidence reports can be downloaded through separate EXCEL files, we combined these EXCEL files into one large file and then converted it to csv format to use as our dataset. This data includes the time and day in which the hate crime ("case") occurred, the location of the crime, the territory where the crime occurred ("beat"), and the type of bias that led to the hate crime. By exploring hate crimes in Sacramento, we set out to see how biases drive hate crimes on a city level during a pivotol time period which includes Trump's presidency and COVID-19 pandemic.

To clean the data, we converted the reported hate crime times from military time to 24 hour time with AM/PM specifications to make it more reader-friendly. We lowercased and condensed most of the headers to one-word titles (e.g. 'Case Number' changed to 'case') to make these variables easier to work with during our exploration. We also lowercased the different biases for a standardarized format because some were written in all upercase letters, while others were written with a mixture of lowercase and uppercase letters. Lastly, we consolidated repetitive biases under one name, for example, we made all "anti-islam" and "anti-muslim" biases "anti-islamic (muslim)." As with the USA dataset exploration, we assigned each bias to a bias category to standardize our analysis.

Data Analysis and Visualization

We explored the following questions to analyze Sacramento hate crimes:

  1. How has the number of hate crimes changed over the years?
  2. How do the numbers of reported hate crimes by bias category change each year?
  3. Within the race/ethnicity ("race/ethn") bias category, how does racial bias change over time?
  4. What are the proportions of bias of reported incidents each year?
  5. What regions in Sacramento (by beat) experienced the most hate crimes?

Sacramento's trend in the total number of hate crimes per year from 2017-2021 shows a general upward trend, with the exception of 2018-2019, and a steep rise in crimes from 2020 to 2021. This could be explained by the fact that the COVID-19 pandemic started in 2020, which not only led to nationwide but city-wide uncertainty and unrest.

SAC_1

When taking a closer look at the rise in number of hate crimes between 2020-2021, it appears that race and ethnicity were the dominant motivators. LGBT-motivated hate crimes also contributed to a fair number of hate crimes during this time period as well. The increase in LGBT hate crimes in 2018 could have been influenced by the major anti-LGBT policies that had been passed by the Trump administration in 2017 (e.g. trans military ban or transgender student guidance reversal according to (Simmons-Duffin 2020), which contribute to anti-LGBT sentiments on a city-scale. A Time article also suggests that the cause of anti-LGBT sentiments sduring the pandemic may stem from a growing number of anti-trans bills and laws that have been passed and enacted (Carlisle 2021).

For the remaining bias categories, the trend in number of hate crimes remained relatively stable for the remaining bias categories.

Total Number of Hate Crimes By Motivation in Sacramento Between 2017-2021 Sacramento Hate Crime Count by Bias Category From 2017-2021
SAC_2 SAC_3

While the previous graph showed that LBGT-motivated hate crimes have been rising since 2020, the proportion of these crimes in relation to the other bias categories is still relatively low (approximately 0.2). On the contrary, the proportion of racially/ethnically-motivated hate crimes drastically spiked in 2019 and stabalized at approximately 0.7 from 2020-2021.

SAC_6

The number of hate crimes motivated by anti-black bias remained the most consistent over time, as racial and ethnic hate crimes committed against African Americans is an ongoing battle. Between 2016 and 2018, there were not any major-publicized police brutality cases. However, we bring to attention highly-publicized police brutality crimes involving Stephon Clark in 2018, George Floyd in 2020, and Daunte Wright in 2021 (BBC 2021). Each of these murders at the hands of police led to city-wide protests as part of the Black Lives Matter movement and anti-black sentiments on a city-scale. While there was a drop in anti-black hate crimes in 2020, there has since been a major rise in crimes.

Hate crimes motivated by anti-other race/ethnicity/national origin tells another story, however. The number of hate crimes motivated by anti-other race/ethnicity/national origin skyrocketed in 2021, the highest it has ever been within the 4 year period. The question of whether hate crimes towards anti-asian/pacific islander increased between 2020-2021 is addressed through this visualization, which shows that the number of hate crimes motivated by this bias relative to other biases strongly increased in 2021. While the number of anti-asian hate crimes wasn't as large as anti-other race/ethnicity/national origin motivated biases (which could still include anti-asian crimes, but the victim's race was not identified during the crime report), it was still prevelant and roughly the same number of hate crimes as anti-black hate crimes in 2018.

As indicated in the stacked barplot, the trend in anti-other race/ethnicity/national origin experienced a major spike between 2020-2021, compared to previous years and other biases. This plot also reaffirms that the trend in anti-black drive hate crimes experienced minimal fluctuations and change over time.

Total Number of Racially-motivated Hate Crimes in Sacramento Between 2017-2021 Change in Number of Hate Crimes By Different Racial Motivation in Sacramento Between 2017-2021
SAC_4 SAC_5

We also wanted to see whether there was a high concentration of hate crimes in certain areas of Sacramento. We did so by plotting coordinates belonging to each beat in Sacramento, which represent the territory or district that the crime occurred in using the SACOG Open Data Portal API (SACOG Data Portal). While we were unable to plot the exact locations using the provided addresses in our dataset due to Google API complications, plotting the hate crimes by their beats gives an approximation of where these hate crimes occurred, which is what we are interested in.

After plotting the hate crimes by beat, we found that the most number of hate crimes occurred in Central (Beats 3A and 3B) and Southwestern (Beats 4A) Sacramento, with the majority of these crimes being racially/ehtnically-motivated. These areas are near downtown Sacramento, and as mentioned in the California analysis, the most number of hate crimes typically occur in more populated regions.

Click for interactive map: Approximate Location of Hate Crimes By Beat, Categorized By Bias from 2017-2021 USmap

Map Color Legend According to Bias Category: blue: "race/ethn"

red: "lgbt"

green: "religion"

yellow: "sex"

orange: "disability"

brown: "other" (mix categories)

Hate Crimes on Social Media, using Reddit's API

Throughout recent years, social media has been a way for people to express their beliefs and interact with others. With the increase in hate crimes, especially in the past five years, social media has served as an avenue for people to simultaneously engage in hateful activities and raise awareness of them. In this portion of the analysis, we will be using Reddit's API to answer the following questions:

  1. In Sacramento specifically, to what extent are hate crimes being discussed on social media?
  2. How does Sacramento's usage of social media to discuss hate crimes compare to the State of California's, in terms of how many posts discuss hate crime and how people respond to them?
  3. Is there a pattern in the language people use when discussing hate crime?

Data Collection + Cleaning

In order to access the data needed for this portion of the analysis, we created a Reddit Account and downloaded PRAW, Python Reddit API Wrapper which allows us to scrape comments and posts from various communities on Reddit, known as subreddits. For this analysis specifically, we will primarily be using the Sacramento and California subreddit. In order to analyze the language contained within these posts, we will also be Natural Language Processing (NLP) techniques using the Pandas and NLTK libraries.

Data Analysis and Visualization

Before delving further into the posts related to hate speech, it may be useful to review Reddit's policies on hate speech. Using Reddit's API, we can access the rules of California and Sacramento's subreddit rules, as shown below.

As we can see from both subreddits, hate speech is banned. From Sacramento's subreddit rules: "Racism, homophobic content and other forms of bigotry are not permitted. Such comments as well as those that threaten or advocate violence or death onto others will result in a ban.

Please comment with civility and do not personally attack others. Spirited debates are great, but if you have to resort to name calling, insults, or personal attacks, you've already lost. Such behavior will result in content removal at a minimum and a ban for repeat offenders."

Similarly, from California's subreddit rules: "* NO insults or incivility, trolling, bigotry, profanity or hate. Nothing that's rude, vulgar or offensive."

Thus, we can see that hate speech is explicitly banned on Reddit. From this, we can further analyze if hate speech still occurs and what people's response to it is.

Now, focusing on Sacramento's subreddit, first we will be using the API and web scraping to get the top 10 posts on the subreddit. Using these, we can analyze what portion of them are linked to hate crime. One important thing to note is that this is dependent on the day. The top 10 posts from the Sacramento subreddit in this analysis are from March 9.

Screen%20Shot%202022-03-14%20at%203.09.18%20PM.png

As we can see from the top 10 posts from the Sacramento subreddit, most of them are not linked to hate crimes. However, two of them stand out from the rest: the fourth one and the seventh one, because they are expressing shock or are related to a racial hate crime. This makes about 80% on the Sacramento subreddit not linked to conflict or hate crimes, based on the top 10 posts.

In order to analyze people's response to the incidence of hate crime, we can delve further into the comments of the post titled "Investigation Underway Into Racially Charged Heckling at El Dorado Hills Soccer Game.

From initially looking at the comments, we can see that a lot of people are asking questions or expressing their opinion on the topic.

To understand the connotations behind the words used, and whether there is a pattern behind them, we are going to be performing NLP, specifically Frequency Analysis.

Screen%20Shot%202022-03-14%20at%204.18.14%20PM.png

The Frequency Analysis shows that there about 617 words in the comments, and though we have lost information about which order the words are in, which is a disadvantage of this technique, we can see that most of the words do not seem to repeat themselves. However, we can see that there are words linked to hate crimes and violence such as "abusers," "shocking" and "disgusting." Yet, from the comments of the post shown earlier, in this instance they are expressing disdain and shock at the incident, not spreading hate.

Something to note is that with this technique, there may be words that are used frequently in the English language. We can also use one-hot encoding which does not account for the frequency of words.

The code snippets above show the individual words from the comments of the post, and the matrix below that contains the corresponding frequencies. From the output, we can see that not many words seem to repeat themselves in the comments.

Therefore, from an analysis of Sacramento's social media using Reddit's API and NLP, we can see that there does not seem to be much hateful language being used. There are words with negative connotations, however we can see from the comments that they are being used mainly in the context of responding with shock to the incidence, not spreading hate. To start off with, not many posts were linked to violence or hate crime in the first place, only 20%.

We can now compare this to the subreddit for the State of California.

Like we did for Sacramento's subreddit, we can get the top 10 most popular posts for California's subreddit.

Screen%20Shot%202022-03-14%20at%205.14.11%20PM.png

Similar to Sacramento, not many of the posts are linked to hate crimes or violence. Out of all of them, the one that seems to be the most linked to racial issues is titled: "California legislators are in agreement: It’s time for the state to repeal a racist, classist provision in the state Constitution that makes it harder to build affordable housing. — Article 34 requires that cities get voter approval before they build “low-rent housing” funded with public dollars."

We can now delve into the comments of the post.

Just from scraping the comments of that post, we can see that most are expressing their opinions on the issue. There do not seem to be many instances of words linked to hate crime, but we can explore this further using NLP.

From performing Frequency Analysis on the comments of the post, we can see which words are used frequently and whether any of them seem to be linked to hate crimes.

Screen%20Shot%202022-03-14%20at%205.34.09%20PM.png

From performing Frequency Analysis, we can see that there are more words with negative connotations than in the comments from Sacramento's subreddit, such as "sneaky" and the last two words in the matrix. Additionally, there seems to be more words linked to race such as "white" and "minority". We can explore this further by obtaining the individual words from the comments.

The words above seem to be more politically or racially linked than the words from the comments on Sacramento's subreddit. From this and the previous analyses, we can see that while California's subreddit contains less posts that are racially or conflict-linked compared to Sacramento's, the words used in California's subreddit are more politically and racially-affiliated. However, in both cases, such language is being used to express disdain on the topic or ask questions, not perform a hate crime.

Lastly, we can also take a look at the top most popular post from the past year on California's subreddit. The top post is titled: "California Defies Doom With No. 1 U.S. Economy" and it has 903 comments. In order to analyze it, I used NLP to tokenize the comments into words. From this, I created a dataframe in which each row is an individual word.

Screen%20Shot%202022-03-14%20at%207.05.15%20PM.png

The plot above shows the most common bigrams from the comments of the post. As we can see, none of them are linked to hate crimes or contain instances of violence.

We can also perform Frequency Analysis on the comments of this post, in order to investigate whether any of the words seem to repeat themselves.

Screen%20Shot%202022-03-14%20at%207.12.32%20PM.png

Similar to the other posts from the State of California and Sacramento's subreddits, here not many words seem to repeat themselves. There also do not appear to be many words with negative connotations. However, something interesting is that there appears to be more numbers such as dates and prices, suggesting that rather than being linked to race, people's discussion of the economy is primarily limited to the scope of the economy. This shows that racial biases do not play much of a role in the discussion of economical issues in California's subreddit.

We can also see what the most popular words in the comments are.

wordcloud.jpg

From the wordcloud above, we can see that the majority of the comments are neutral and do not have any racial or other hate speech linked negative connotations. The most common words seem to be "state", "California", "like" and "people." Thus even on a post that discusses economic issues, people still tend to use neutral language.

Conclusion

Looking at the national and state level, we find that changes in the number of hate crime due to race/ethnicity bias consistently drive the changes seen on the overall number of hate crime. A higher number of hate crime across state and county levels seems to be associated with a higher population. The recent uptick in the number of hate crime due to race/ethnicity bias coincide with the COVID-19 pandemic. As such, we found an increase in the number of hate crimes targeting Asians, due to the negative sentiment and attitude regarding COVID-19's origin in China.

Now understanding what motivates hate crime, we looked towards social media to see how people respond to hate crime. Ultimately, from the analysis of social media using Reddit's API and Natural Language Processing for the State of California and Sacramento, we can draw the following conclusions:

  1. Majority of the posts are not linked to instances of hate crimes. In Sacramento, 20% were whereas for California it was 10%.
  2. When responding to posts containing instances of hate speech or racially linked incidents, people do not use language with racial or negative connotations. If they do, it's to raise awareness of the topic and share their opinion, not spread hate generally.
  3. This does not mean that hate speech does not occur. However, for the most part, as a whole language used in California and Sacramento's subreddit is neutral.

Bibliography

  1. Hernandez J. Hate crimes reach the highest level in more than a decade. NPR. https://www.npr.org/2021/08/31/1032932257/hate-crimes-reach-the-highest-level-in-more-than-a-decade. Published September 1, 2021. Accessed February 13, 2022.
  2. Hate crime statistics. Published August 30, 2021. Accessed February 13, 2022. https://www.justice.gov/hatecrimes/hate-crime-statistics
  3. Müller K, Schwarz C. Fanning the flames of hate: social media and hate crime. Journal of the European Economic Association. 2021;19(4):2131-2167. doi:10.1093/jeea/jvaa045
  4. Anguiano D. SF police data shows 567% increase in reports of hate crimes against Asian Americans. The Guardian. https://www.theguardian.com/us-news/2022/jan/26/san-francisco-increase-hate-crime-anti-asian-aapi. Published January 26, 2022. Accessed February 13, 2022.
  5. Crime Data Explorer. Accessed March 14, 2022. https://crime-data-explorer.app.cloud.gov/pages/downloads
  6. Population of counties in california(2022). Accessed March 14, 2022. https://worldpopulationreview.com/us-counties/states/ca
  7. California Counties. https://www.counties.org/sites/main/files/file-attachments/2020-june3-countycaucusesinfographic-4-final.pdf
  8. Cabral S. Covid “hate crimes” against Asian Americans on rise. BBC News. https://www.bbc.com/news/world-us-canada-56218684. Published May 21, 2021. Accessed March 14, 2022.
  9. Racial resentment and whites’ feelings toward black lives matter: a q&a with dr. Emmitt y. Riley, iii. UC Press Blog. Accessed March 14, 2022. https://www.ucpress.edu/blog/54246/racial-resentment-and-whites-feelings-toward-black-lives-matter-a-qa-with-dr-emmitt-y-riley-iii/
  10. Hay M. ‘Anti-white watch’ is the racist answer to surging hate crimes. The Daily Beast. https://www.thedailybeast.com/anti-white-watch-is-the-racist-answer-to-hate-crimes. Published May 11, 2021. Accessed March 14, 2022.
  11. Us states - ranked by population 2022. Accessed March 14, 2022. https://worldpopulationreview.com/states
  12. U.S. Hispanic population, by state 2019. Statista. Accessed March 14, 2022. https://www.statista.com/statistics/259850/hispanic-population-of-the-us-by-state/
  13. Asian american population by state 2022. Accessed March 14, 2022. https://worldpopulationreview.com/state-rankings/asian-population
  14. Cosgrove Jacyln. L.A. County reports 76% increase in anti-Asian hate crimes. Los Angeles Times. Published October 21, 2021. Accessed March 14, 2022. https://www.latimes.com/california/story/2021-10-20/l-a-county-sees-significant-increase-in-anti-asian-hate-crimes
  15. Mizes-Tan S. ‘We have been targeted’: sacramento asian american community demands more support, unity after atlanta killings. Published 2021. Accessed March 14, 2022. https://www.capradio.org/163655
  16. California counties by population. Accessed March 14, 2022. https://www.california-demographics.com/counties_by_population
  17. Convert a List to Pandas Dataframe (with examples). Accessed March 14, 2022. https://datatofish.com/list-to-dataframe/
  18. Exploratory Data Analysis for Natural Language Processing: A Complete Guide to Python Tools. Accessed March 14, 2022. https://neptune.ai/blog/exploratory-data-analysis-natural-language-processing-tools
  19. WordClouds.com. Accessed March 14, 2022. WordClouds.com
  20. Scraping Reddit using Python. Accessed March 14, 2022. Scraping Reddit using Python.
  21. Reddit API with Python (Complete Guide). Accessed March 14, 2022. https://www.jcchouinard.com/reddit-api/
  22. Reddit API documentation. Accessed March 14, 2022. https://www.reddit.com/dev/api#GET_top.
  23. SACOG Open Data Portal API. Accessed March 14, 2022. https://data.sacog.org/datasets/0d7615bf9b1e47948046a82b261d2384_0/about
  24. Carlisle Madeline. Anti-Trans Violence and Rhetoric Reached Record Highs Across America in 2021. Time. https://time.com/6131444/2021-anti-trans-violence/. Published December 30, 2021. Accessed March 14, 2022.
  25. City of Sacramento Police Department. http://www.cityofsacramento.org/police/crime. Accessed March 14, 2022.
  26. Simmons-Duffin, Selena. 'Whiplash' Of LGBTQ Protections And Rights, From Obama To Trump. npr. https://www.npr.org/sections/health-shots/2020/03/02/804873211/whiplash-of-lgbtq-protections-and-rights-from-obama-to-trump. Published March 2, 2020. Accessed March 14, 2022.
  27. Online Reddit API documentation/resources.
  28. Lecture notes.

Code

Data cleaning of FBI's 1991-2020 Hate Crime Dataset

Hate Crime at the U.S. level

Hate Crime at the CA level

Data cleaning 2020_CA_city_to_county.csv dataset

Creating CA only hate crime dataset with county information from 2020_CA_city_to county.csv

Data Analysis and Visualization

Hate Crime at the U.S. level

How has the number of hate crimes changed over the years?

How do the numbers of reported hate crimes by bias category change each year?

Within the race/ethnicity ("race/ethn") bias category, how does racial bias change over time?

How much did the number of hate crime incidents by race/ethnicity change from 2019 to 2020?

In each state, how many hate crimes due to race/ethnicity has there been in total since 1991 until 2020?

In each state, how many hate crimes due to race/ethnicity are there in 2020?

Hate Crime at the CA level

How has the number of hate crimes changed over the years in CA?

How do the numbers of reported hate crimes by bias category change each year?

Within the race/ethnicity ("race/ethn") bias category, how does racial bias change over time?

How much did the number of hate crime incidents by racial motivations change from 2019 to 2020?

What are the major biases motivating hate crime in urban, suburban, and rural counties?

Does the number of hate crime motivated by race/ethnicity vary between urban, suburban, and rural counties?

In each county in CA, how many hate crimes due to race/ethnicity are there in total since 1991?

In each county in CA, how many hate crimes due to race/ethnicity are there in 2020?

Data cleaning of Sacramento Police Department Incidence Report Dataset from 2017-2021

Hate Crime at the Sacramento Level

How has the number of hate crimes changed over the years in Sacramento?

How do the numbers of reported hate crimes by bias category change each year?

What are the proportions of bias of reported incidents each year?

Within the race/ethnicity ("race/ethn") bias category, how does racial bias change over time?

Within each bias category, which bias against which group is most prevalent?

Which bias category and biases are most prevalent each year?

What regions in Sacramento (by beat) experienced the most hate crimes?

Analysis using Reddit's API